modelbased: Estimation of Model-Based Predictions, Contrasts and Means

Implements a general interface for model-based estimations for a wide variety of models (see support list of insight; Lüdecke, Waggoner & Makowski (2019) <doi:10.21105/joss.01412>), used in the computation of marginal means, contrast analysis and predictions.

Version: 0.3.0
Imports: insight (≥ 0.7.1), bayestestR (≥ 0.4.0), parameters (≥ 0.3.0), emmeans (≥ 1.4.4), graphics, stats, utils
Suggests: coda, covr, dplyr, effectsize, gganimate, ggplot2, glmmTMB, knitr, lme4, logspline, MASS, merTools, mgcv, rmarkdown, rstanarm, brms, see, testthat
Published: 2020-09-27
Author: Dominique Makowski ORCID iD [aut, cre], Daniel Lüdecke ORCID iD [aut], Mattan S. Ben-Shachar ORCID iD [aut]
Maintainer: Dominique Makowski <dom.makowski at gmail.com>
BugReports: https://github.com/easystats/modelbased/issues
License: GPL-3
URL: https://github.com/easystats/modelbased
NeedsCompilation: no
Citation: modelbased citation info
Materials: README NEWS
CRAN checks: modelbased results

Downloads:

Reference manual: modelbased.pdf
Package source: modelbased_0.3.0.tar.gz
Windows binaries: r-devel: modelbased_0.3.0.zip, r-release: modelbased_0.1.2.zip, r-oldrel: modelbased_0.3.0.zip
macOS binaries: r-release: modelbased_0.3.0.tgz, r-oldrel: modelbased_0.1.2.tgz
Old sources: modelbased archive

Reverse dependencies:

Reverse suggests: bayestestR, effectsize, see

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